On second order duality of minimax fractional programming with square root term involving generalized B-(p, r)-invex functions

2016 ◽  
Vol 244 (2) ◽  
pp. 603-617 ◽  
Author(s):  
Sonali ◽  
N. Kailey ◽  
V. Sharma
Keyword(s):  
Fractional Programming ◽  
Second Order ◽  
Square Root ◽  
Invex Functions ◽  
Second Order Duality ◽  
Minimax Fractional Programming ◽  
Root Term

scholarly journals Second Order Duality in Multiobjective Fractional Programming with Square Root Term under Generalized Univex Function

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Arun Kumar Tripathy
Keyword(s):  
Fractional Programming ◽  
Sufficient Conditions ◽  
Positive Semidefinite ◽  
Second Order ◽  
Square Root ◽  
Multiobjective Fractional Programming ◽  
Multiobjective Fractional Programming Problem ◽  
Second Order Duality ◽  
Root Term ◽  
Necessary And Sufficient

Three approaches of second order mixed type duality are introduced for a nondifferentiable multiobjective fractional programming problem in which the numerator and denominator of objective function contain square root of positive semidefinite quadratic form. Also, the necessary and sufficient conditions of efficient solution for fractional programming are established and a parameterization technique is used to establish duality results under generalized second order ρ-univexity assumption.

scholarly journals On Second-Order Duality for Minimax Fractional Programming Problems with Generalized Convexity

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Izhar Ahmad
Keyword(s):  
Programming Problem ◽  
Fractional Programming ◽  
Generalized Convexity ◽  
Second Order ◽  
Fractional Programming Problem ◽  
Second Order Duality ◽  
Minimax Fractional Programming ◽  
Dual Models

We focus our study on a discussion of duality relationships of a minimax fractional programming problem with its two types of second-order dual models under the second-order generalized convexity type assumptions. Results obtained in this paper naturally unify and extend some previously known results on minimax fractional programming in the literature.

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